• Design & Manufacturing
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• v.14 no.1
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• pp.63-68
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• 2020

Ultra-high brightness and thin displays need to optical micro-patterns which can uniformly diffuse the lights and low loss. The micro random patterns have characteristics to rise the optical efficiency such as light extraction, uniform diffusion. For this reason, various fabrication processes are studied for random patterns. In this study, the micro random patterns were machined by diamond turning which used a controlled cutting tool path with random cutting depth. The machined patterns had random shape and directionality along the circumferential direction. The average width and length of machined random pattern according to rotation radius were 40.13㎛~55.51㎛ and 37.25㎛~59.49㎛, and these results were compared with the designed result. Also, the machining error according to rotation radius in diamond turning using randomly controlled cutting depth was discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1189-1204
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• 2018

Detecting and capturing 3D human structures from the intensity-based image sequences is an inherently arguable problem, which attracted attention of several researchers especially in real-time activity recognition (Real-AR). These Real-AR systems have been significantly enhanced by using depth intensity sensors that gives maximum information, in spite of the fact that conventional Real-AR systems are using RGB video sensors. This study proposed a depth-based routine-logging Real-AR system to identify the daily human activity routines and to make these surroundings an intelligent living space. Our real-time routine-logging Real-AR system is categorized into two categories. The data collection with the use of a depth camera, feature extraction based on joint information and training/recognition of each activity. In-addition, the recognition mechanism locates, and pinpoints the learned activities and induces routine-logs. The evaluation applied on the depth datasets (self-annotated and MSRAction3D datasets) demonstrated that proposed system can achieve better recognition rates and robust as compare to state-of-the-art methods. Our Real-AR should be feasibly accessible and permanently used in behavior monitoring applications, humanoid-robot systems and e-medical therapy systems.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.6
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• pp.605-612
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• 2015

Three dimensional (3D) position determination and motion recognition using a 3D depth sensor camera are applied to a developed penguin-shaped robot, and its validity and closeness are investigated. The robot is equipped with an Asus Xtion Pro Live as a 3D depth camera, and a sound module. Using the skeleton information from the motion recognition data extracted from the camera, the robot is controlled so as to follow the typical three mode-reactions formed by the operator's gestures. In this study, the extraction of skeleton joint information using the 3D depth camera is introduced, and the tracking performance of the operator's motions is explained.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.12
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• pp.1089-1093
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• 2013

Depth extraction using the structured illumination method is popularly applied since it has the benefit of measuring the object without contact. With multiple spatial frequencies and phase-shifting techniques, it is possible to extract the depth of objects with large discontinuity. For applications such as 3D (Three Dimensional) displays, 3D information of the object is required and is useful if corresponding to each view of the display. For this purpose, hypercentric optics is appropriate to measure the depth information of an object with a large field of view that is applicable for a 3D display. By experiment, we present the feasibility for phase-shifting profilometry using hypercentric optics to obtain the depth information of an object with the field of view appropriate for a 3D display.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.345-352
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• 2013

In this paper, a depth estimate method is proposed using GPU(Graphics Processing Unit) in monocular image. a monocular image is a 2D image with missing 3D depth information due to the camera projection and we used a monocular cue to recover the lost depth information by the projection present. The proposed algorithm uses an energy function which takes a variety of cues to create a more generalized and reliable depth map. But, a processing time is late because energy function is defined from the various monocular cues. Therefore, we propose a depth estimate method using GPGPU(General Purpose Graphics Processing Unit). The objective effectiveness of the algorithm is shown using PSNR(Peak Signal to Noise Ratio), a processing time is decrease by 61.22%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.3
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• pp.384-390
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• 2020

The reverberation effect on the sound when producing movies or VR contents is a very important factor in the realism and liveliness. The reverberation time depending the space is recommended in a standard called RT60(Reverberation Time 60 dB). In this paper, we propose a scene recognition technique for automatic reverberation editing. To this end, we devised a classification model that independently trains color images and predicted depth images in the same model. Indoor scene classification is limited only by training color information because of the similarity of internal structure. Deep learning based depth information extraction technology is used to use spatial depth information. Based on RT60, 10 scene classes were constructed and model training and evaluation were conducted. Finally, the proposed SCR + DNet (Scene Classification for Reverb + Depth Net) classifier achieves higher performance than conventional CNN classifiers with 92.4% accuracy.

• The Journal of the Korean dental association
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• v.58 no.6
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• pp.336-345
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• 2020

Peri-apical implant lesion, also known as 'retrograde peri-implantitis' can occur with multifactorial etiological factors. The purpose of this case report is to demonstrate resolution of periapical implant lesion by removal of causative factors and saving implant by regenerative therapy. A 54-year old male patient with mild dull pain around implant on the right mandibular second premolar area due to persistent peri-apical infection of the adjacent first premolar was treated. Extraction of tooth with symptomatic apical periodontitis and regenerative therapy on the buccal fenestration area of the implant and extraction site were performed. After 6-month reentry, notable regenerated bone tissue around implant was found, and implant placement on the previous extraction site was performed. After 14-month follow-up from the regenerative therapy, neither biological nor mechanical complication could be found around the implant, evidenced by high implant stability, normal clinical probing depth, and absence of discomfort spontaneously and during masticatory function. In conclusion, surgical intervention including regenerative therapy using bone graft and barrier membrane on periapical implant lesion can be suggested as one of the treatment options considering the extent of periapical lesion.

• Journal of Dental Anesthesia and Pain Medicine
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• v.24 no.1
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• pp.75-80
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• 2024

Dental sedation plays a pivotal role in alleviating patient anxiety during various procedures. Remimazolam, a benzodiazepine derivative, stands out for its distinctive attributes, particularly its rapid onset of sedation coupled with a brief duration, making it an invaluable option for dental applications. The patient was admitted for the extraction of impacted third molars via patient-controlled sedation and not only demonstrated stable vital signs but also expressed a high level of satisfaction with the procedure. An in-depth analysis of plasma remimazolam concentrations and changes in the Patient State Index revealed negative correlation patterns, highlighting the inherent potential of remimazolam in achieving effective sedation. This expanded research scope aims to provide a more nuanced understanding of the pharmacological responses to remimazolam in dental sedation scenarios. This case report offers valuable insights into the evolving landscape of dental sedation methodologies and paves the way for a more informed and evidence-based approach to the use of remimazolam in patient-controlled sedation.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.40-43
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• 1997

This paper presents a 3D object recognition method for generation of 3D environmental map or obstacle recognition of mobile robots. An active light source projects a stripe pattern of light onto the object surface, while the camera observes the projected pattern from its offset point. The system consists of a laser unit and a camera on a pan/tilt device. The line segment in 2D camera image implies an object surface plane. The scaling, filtering, edge extraction, object extraction and line thinning are used for the enhancement of the light stripe image. We can get faithful depth informations of the object surface from the line segment interpretation. The performance of the proposed method has demonstrated in detail through the experiments for varies type objects. Experimental results show that the method has a good position accuracy, effectively eliminates optical noises in the image, greatly reduces memory requirement, and also greatly cut down the image processing time for the 3D object recognition compared to the conventional object recognition.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.7
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• pp.1224-1230
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• 2007

In this paper, we study the classification of defects at steam generator tube in nuclear power plant using eddy current testing (ECT). We consider 4 defect patterns of SG tube: I-In type, I-Out type, V-In type, and V-Out type. Through numerical analysis program based on finite element modeling, 400 ECT signals are generated by varying width and depth of each defect type. In order to improve the classification performance, we propose new feature extraction technique. After extracting new features from the generated ECT signals, multi-layer perceptron is used to classify the defect patterns. Through the computer simulation study, it is shown that the proposed method achieves 100% classification success rate while the previous method yields 91% success rate.